Comparing multi-server queues with finite waiting rooms, I: Same number of servers

1979 ◽  
Vol 11 (2) ◽  
pp. 439-447 ◽  
Author(s):  
David Sonderman
Keyword(s):  
Queueing Systems ◽  
Stochastic Comparisons ◽  
Waiting Room ◽  
Service Times ◽  
Interarrival Times ◽  
Multi Server

We compare two queueing systems with the same number of servers that differ by having stochastically ordered service times and/or interarrival times as well as different waiting room capacities. We establish comparisons for the sequences of actual-arrival and departure epochs, and demonstrate by counterexample that many stochastic comparisons possible with infinite waiting rooms no longer hold with finite waiting rooms.

Comparing multi-server queues with finite waiting rooms, I: Same number of servers

1979 ◽  
Vol 11 (02) ◽  
pp. 439-447 ◽  
Author(s):  
David Sonderman
Keyword(s):  
Queueing Systems ◽  
Stochastic Comparisons ◽  
Waiting Room ◽  
Service Times ◽  
Interarrival Times ◽  
Multi Server

We compare two queueing systems with the same number of servers that differ by having stochastically ordered service times and/or interarrival times as well as different waiting room capacities. We establish comparisons for the sequences of actual-arrival and departure epochs, and demonstrate by counterexample that many stochastic comparisons possible with infinite waiting rooms no longer hold with finite waiting rooms.

Comparing multi-server queues with finite waiting rooms, II: Different numbers of servers

1979 ◽  
Vol 11 (02) ◽  
pp. 448-455 ◽  
Author(s):  
David Sonderman
Keyword(s):  
Probability Space ◽  
Queueing Systems ◽  
Stochastic Order ◽  
Sample Path ◽  
System Size ◽  
Waiting Room ◽  
Virtual Waiting Time ◽  
Number Of Customers ◽  
Multi Server ◽  
Quantities Of Interest

We compare two queueing systems with identical general arrival streams, but different numbers of servers, different waiting room capacities, and stochastically ordered service time distributions. Under appropriate conditions, it is possible to construct two new systems on the same probability space so that the new systems are probabilistically equivalent to the original systems and each sample path of the stochastic process representing system size in one system lies entirely below the corresponding sample path in the other system. This construction implies stochastic order for these processes and many associated quantities of interest, such as a busy period, the number of customers lost in any interval, and the virtual waiting time.

Queueing output processes

1976 ◽  
Vol 8 (2) ◽  
pp. 395-415 ◽  
Author(s):  
D. J. Daley
Keyword(s):  
Queueing Systems ◽  
Second Order ◽  
Arrival Process ◽  
Single Server ◽  
Stationary Condition ◽  
Waiting Room ◽  
Stationary Point Process ◽  
Poisson Arrivals ◽  
Service Times ◽  
Markovian Systems

The paper reviews various aspects, mostly mathematical, concerning the output or departure process of a general queueing system G/G/s/N with general arrival process, mutually independent service times, s servers (1 ≦ s ≦ ∞), and waiting room of size N (0 ≦ N ≦ ∞), subject to the assumption of being in a stable stationary condition. Known explicit results for the distribution of the stationary inter-departure intervals {Dn} for both infinite and finite-server systems are given, with some discussion on the use of reversibility in Markovian systems. Some detailed results for certain modified single-server M/G/1 systems are also available. Most of the known second-order properties of {Dn} depend on knowing that the system has either Poisson arrivals or exponential service times. The related stationary point process for which {Dn} is the stationary sequence of the corresponding Palm–Khinchin distribution is introduced and some of its second-order properties described. The final topic discussed concerns identifiability, and questions of characterizations of queueing systems in terms of the output process being a renewal process, or uncorrelated, or infinitely divisible.

Queueing output processes

1976 ◽  
Vol 8 (02) ◽  
pp. 395-415 ◽  
Author(s):  
D. J. Daley
Keyword(s):  
Queueing Systems ◽  
Second Order ◽  
Arrival Process ◽  
Single Server ◽  
Stationary Condition ◽  
Waiting Room ◽  
Stationary Point Process ◽  
Poisson Arrivals ◽  
Service Times ◽  
Markovian Systems

The paper reviews various aspects, mostly mathematical, concerning the output or departure process of a general queueing systemG/G/s/Nwith general arrival process, mutually independent service times,sservers (1 ≦s≦ ∞), and waiting room of sizeN(0 ≦N≦ ∞), subject to the assumption of being in a stable stationary condition. Known explicit results for the distribution of the stationary inter-departure intervals {Dn} for both infinite and finite-server systems are given, with some discussion on the use of reversibility in Markovian systems. Some detailed results for certain modified single-serverM/G/1 systems are also available. Most of the known second-order properties of {Dn} depend on knowing that the system has either Poisson arrivals or exponential service times. The related stationary point process for which {Dn} is the stationary sequence of the corresponding Palm–Khinchin distribution is introduced and some of its second-order properties described. The final topic discussed concerns identifiability, and questions of characterizations of queueing systems in terms of the output process being a renewal process, or uncorrelated, or infinitely divisible.

Comparing multi-server queues with finite waiting rooms, II: Different numbers of servers

1979 ◽  
Vol 11 (2) ◽  
pp. 448-455 ◽  
Author(s):  
David Sonderman
Keyword(s):  
Probability Space ◽  
Queueing Systems ◽  
Stochastic Order ◽  
Sample Path ◽  
System Size ◽  
Waiting Room ◽  
Virtual Waiting Time ◽  
Number Of Customers ◽  
Multi Server ◽  
Quantities Of Interest

We compare two queueing systems with identical general arrival streams, but different numbers of servers, different waiting room capacities, and stochastically ordered service time distributions. Under appropriate conditions, it is possible to construct two new systems on the same probability space so that the new systems are probabilistically equivalent to the original systems and each sample path of the stochastic process representing system size in one system lies entirely below the corresponding sample path in the other system. This construction implies stochastic order for these processes and many associated quantities of interest, such as a busy period, the number of customers lost in any interval, and the virtual waiting time.

scholarly journals Comments on a Two Queue Network

2017 ◽  
Vol 6 (6) ◽  
pp. 43
Author(s):  
Samantha Morin ◽  
Myron Hlynka ◽  
Shan Xu
Keyword(s):  
Service Time ◽  
Queueing System ◽  
Queueing Systems ◽  
Time To Completion ◽  
Time Parameters ◽  
Service Times ◽  
Interarrival Times

A special customer must complete service from two servers, each with an $M/M/1$ queueing system. It is assumed that the two queueing systems have initiial numbers of customers $a$ and $b$ at the instant when the special customer arrives, and subsequent interarrival times and service times are independent. We find the expected total time (ETT) for the special customer to complete service. We show that even if the interarrival and service time parameters of two queues are identical, there exist examples (specific values of the parameters and initial lengths a and b) for which the special customer surprisingly has a lower expected total time to completion by joining the longer queue first rather than the shorter one.

Approximate solution for multi-server queueing systems with Erlangian service times

2002 ◽  
Vol 29 (10) ◽  
pp. 1353-1374 ◽  
Author(s):  
Marcos Escobar ◽  
Amedeo R. Odoni ◽  
Emily Roth
Keyword(s):  
Approximate Solution ◽  
Queueing Systems ◽  
Erlangian Service Times ◽  
Service Times ◽  
Multi Server

scholarly journals Zero Queueing for Multi-Server Jobs

2021 ◽  
Vol 5 (1) ◽  
pp. 1-25
Author(s):  
Weina Wang ◽  
Qiaomin Xie ◽  
Mor Harchol-Balter
Keyword(s):  
Cloud Computing ◽  
Stability Region ◽  
Transient Analysis ◽  
Queueing Systems ◽  
Sufficient Conditions ◽  
Hard Problem ◽  
Queueing Model ◽  
Multiple Servers ◽  
First Results ◽  
Multi Server

Cloud computing today is dominated by multi-server jobs. These are jobs that request multiple servers simultaneously and hold onto all of these servers for the duration of the job. Multi-server jobs add a lot of complexity to the traditional one-server-per-job model: an arrival might not "fit'' into the available servers and might have to queue, blocking later arrivals and leaving servers idle. From a queueing perspective, almost nothing is understood about multi-server job queueing systems; even understanding the exact stability region is a very hard problem. In this paper, we investigate a multi-server job queueing model under scaling regimes where the number of servers in the system grows. Specifically, we consider a system with multiple classes of jobs, where jobs from different classes can request different numbers of servers and have different service time distributions, and jobs are served in first-come-first-served order. The multi-server job model opens up new scaling regimes where both the number of servers that a job needs and the system load scale with the total number of servers. Within these scaling regimes, we derive the first results on stability, queueing probability, and the transient analysis of the number of jobs in the system for each class. In particular we derive sufficient conditions for zero queueing. Our analysis introduces a novel way of extracting information from the Lyapunov drift, which can be applicable to a broader scope of problems in queueing systems.

On queueing systems by retrials

1983 ◽  
Vol 20 (02) ◽  
pp. 380-389 ◽  
Author(s):  
Vidyadhar G. Kulkarni
Keyword(s):  
General Result ◽  
Service Time ◽  
Queueing Systems ◽  
Single Server ◽  
Expected Number ◽  
Waiting Room ◽  
Second Moments ◽  
Different Types ◽  
General Distributions ◽  
Arbitrary Service Time

A general result for queueing systems with retrials is presented. This result relates the expected total number of retrials conducted by an arbitrary customer to the expected total number of retrials that take place during an arbitrary service time. This result is used in the analysis of a special system where two types of customer arrive in an independent Poisson fashion at a single-server service station with no waiting room. The service times of the two types of customer have independent general distributions with finite second moments. When the incoming customer finds the server busy he immediately leaves and tries his luck again after an exponential amount of time. The retrial rates are different for different types of customers. Expressions are derived for the expected number of retrial customers of each type.

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